Is "nb_steps_warmup" set for each episode or globally?
When I configure a DQN agent, nb_steps_warmup
can be set. Is this parameter set for each episode or once globally?
What I am trying to ask is, imaging I have a game environment which takes about 3000 max. steps per episode
. The DQN is fitted as follows:
dqn.fit(env, nb_steps=30000, visualize=True, verbose=2)
So, as I understand it, the fitting will run approximately 10 episodes (nb_steps / max. steps per episode
).
If I set nb_steps_warmup = 5000
, what actually happens?
A) nb_steps_warmup=5000
, so 5000 out of nb_steps=30000
are used for warming up
B) within each episode the first nb_steps_warmup=5000
steps are used for warm up. As nb_steps_warmup
max. steps per episode
, the complete episode is used for warming up, which essentially means the fitting never leaves the warming up phase.
C) sth. else?
Topic keras-rl keras reinforcement-learning python
Category Data Science